The SCIP Optimization Suite 6.0

Ambros Gleixner; Michael Bastubbe; Leon Eifler; Tristan Gally; Robert Lion Gottwald; Gregor Hendel; Christopher Hojny; Thorsten Koch; Marco E. Lübbecke; Stephen J. Maher; Matthias Miltenberger; Benjamin Müller; Marc E. Pfetsch; Christian Puchert; Daniel Rehfeldt; Franziska Schlösser; Christoph Schubert; Felipe Serrano; Yuji Shinano; Jan Merlin Viernickel; Matthias Walter; Fabian Wegscheider; Jonas T. Witt; Jakob Witzig

The SCIP Optimization Suite 6.0

Ambros Gleixner, Michael Bastubbe, Leon Eifler, Tristan Gally, Robert Lion Gottwald, Gregor Hendel, Christopher Hojny, Thorsten Koch, Marco E. Lübbecke, Stephen J. Maher, Matthias Miltenberger, Benjamin Müller, Marc E. Pfetsch, Christian Puchert, Daniel Rehfeldt, Franziska Schlösser, Christoph Schubert, Felipe Serrano, Yuji Shinano, Jan Merlin ViernickelMatthias Walter, Fabian Wegscheider, Jonas T. Witt, Jakob Witzig

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The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 6.0 of the SCIP Optimization Suite. Besides performance improvements of the MIP and MINLP core achieved by new primal heuristics and a new selection criterion for cutting planes, one focus of this release are decomposition algorithms. Both SCIP and the automatic decomposition solver GCG now include advanced functionality for performing Benders’ decomposition in a generic framework. GCG’s detection loop for structured matrices and the coordination of pricing routines for Dantzig-Wolfe decomposition has been significantly revised for greater flexibility. Two SCIP extensions have been added to solve the recursive circle packing problem by a problem-specific column generation scheme and to demonstrate the use of the new Benders’ framework for stochastic capacitated facility location. Last, not least, the report presents updates and additions to the other components and extensions of the SCIP Optimization Suite: the LP solver SoPlex, the modeling language Zimpl, the parallelization framework UG, the Steiner tree solver SCIP-Jack, and the mixed-integer semidefinite programming solver SCIP-SDP.

Originele taal-2	Engels
Uitgeverij	Zuse Institut Berlin
Aantal pagina's	42
Status	Gepubliceerd - 2018
Extern gepubliceerd	Ja

Publicatie series

Naam	ZIB Report
Uitgeverij	Zuse Institute Berlin
ISSN van geprinte versie	1438-0064
ISSN van elektronische versie	2192-7782

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Publishers versionDefinitieve gepubliceerde versie, 1,67 MB

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@book{47b428f160044ec5a8e2143e3fe0abbd,

title = "The SCIP Optimization Suite 6.0",

abstract = "The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 6.0 of the SCIP Optimization Suite. Besides performance improvements of the MIP and MINLP core achieved by new primal heuristics and a new selection criterion for cutting planes, one focus of this release are decomposition algorithms. Both SCIP and the automatic decomposition solver GCG now include advanced functionality for performing Benders{\textquoteright} decomposition in a generic framework. GCG{\textquoteright}s detection loop for structured matrices and the coordination of pricing routines for Dantzig-Wolfe decomposition has been significantly revised for greater flexibility. Two SCIP extensions have been added to solve the recursive circle packing problem by a problem-specific column generation scheme and to demonstrate the use of the new Benders{\textquoteright} framework for stochastic capacitated facility location. Last, not least, the report presents updates and additions to the other components and extensions of the SCIP Optimization Suite: the LP solver SoPlex, the modeling language Zimpl, the parallelization framework UG, the Steiner tree solver SCIP-Jack, and the mixed-integer semidefinite programming solver SCIP-SDP.",

author = "Ambros Gleixner and Michael Bastubbe and Leon Eifler and Tristan Gally and Gottwald, {Robert Lion} and Gregor Hendel and Christopher Hojny and Thorsten Koch and L{\"u}bbecke, {Marco E.} and Maher, {Stephen J.} and Matthias Miltenberger and Benjamin M{\"u}ller and Pfetsch, {Marc E.} and Christian Puchert and Daniel Rehfeldt and Franziska Schl{\"o}sser and Christoph Schubert and Felipe Serrano and Yuji Shinano and Viernickel, {Jan Merlin} and Matthias Walter and Fabian Wegscheider and Witt, {Jonas T.} and Jakob Witzig",

year = "2018",

language = "English",

series = "ZIB Report",

publisher = "Zuse Institut Berlin",

}

Gleixner, A, Bastubbe, M, Eifler, L, Gally, T, Gottwald, RL, Hendel, G, Hojny, C, Koch, T, Lübbecke, ME, Maher, SJ, Miltenberger, M, Müller, B, Pfetsch, ME, Puchert, C, Rehfeldt, D, Schlösser, F, Schubert, C, Serrano, F, Shinano, Y, Viernickel, JM, Walter, M, Wegscheider, F, Witt, JT & Witzig, J 2018, The SCIP Optimization Suite 6.0. ZIB Report, Zuse Institut Berlin.

TY - BOOK

T1 - The SCIP Optimization Suite 6.0

AU - Gleixner, Ambros

AU - Bastubbe, Michael

AU - Eifler, Leon

AU - Gally, Tristan

AU - Gottwald, Robert Lion

AU - Hendel, Gregor

AU - Hojny, Christopher

AU - Koch, Thorsten

AU - Lübbecke, Marco E.

AU - Maher, Stephen J.

AU - Miltenberger, Matthias

AU - Müller, Benjamin

AU - Pfetsch, Marc E.

AU - Puchert, Christian

AU - Rehfeldt, Daniel

AU - Schlösser, Franziska

AU - Schubert, Christoph

AU - Serrano, Felipe

AU - Shinano, Yuji

AU - Viernickel, Jan Merlin

AU - Walter, Matthias

AU - Wegscheider, Fabian

AU - Witt, Jonas T.

AU - Witzig, Jakob

PY - 2018

Y1 - 2018

N2 - The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 6.0 of the SCIP Optimization Suite. Besides performance improvements of the MIP and MINLP core achieved by new primal heuristics and a new selection criterion for cutting planes, one focus of this release are decomposition algorithms. Both SCIP and the automatic decomposition solver GCG now include advanced functionality for performing Benders’ decomposition in a generic framework. GCG’s detection loop for structured matrices and the coordination of pricing routines for Dantzig-Wolfe decomposition has been significantly revised for greater flexibility. Two SCIP extensions have been added to solve the recursive circle packing problem by a problem-specific column generation scheme and to demonstrate the use of the new Benders’ framework for stochastic capacitated facility location. Last, not least, the report presents updates and additions to the other components and extensions of the SCIP Optimization Suite: the LP solver SoPlex, the modeling language Zimpl, the parallelization framework UG, the Steiner tree solver SCIP-Jack, and the mixed-integer semidefinite programming solver SCIP-SDP.

AB - The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 6.0 of the SCIP Optimization Suite. Besides performance improvements of the MIP and MINLP core achieved by new primal heuristics and a new selection criterion for cutting planes, one focus of this release are decomposition algorithms. Both SCIP and the automatic decomposition solver GCG now include advanced functionality for performing Benders’ decomposition in a generic framework. GCG’s detection loop for structured matrices and the coordination of pricing routines for Dantzig-Wolfe decomposition has been significantly revised for greater flexibility. Two SCIP extensions have been added to solve the recursive circle packing problem by a problem-specific column generation scheme and to demonstrate the use of the new Benders’ framework for stochastic capacitated facility location. Last, not least, the report presents updates and additions to the other components and extensions of the SCIP Optimization Suite: the LP solver SoPlex, the modeling language Zimpl, the parallelization framework UG, the Steiner tree solver SCIP-Jack, and the mixed-integer semidefinite programming solver SCIP-SDP.

The SCIP Optimization Suite 6.0

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